Real-time End-to-End Federated Learning: An Automotive Case Study

22 March 2021

Papers citing "Real-time End-to-End Federated Learning: An Automotive Case Study"

8 / 8 papers shown

Title
A Numerical Gradient Inversion Attack in Variational Quantum Neural-Networks Georgios Papadopoulos Shaltiel Eloul Yash Satsangi Jamie Heredge Niraj Kumar Chun-Fu Chen Marco Pistoia 55 0 0 17 Apr 2025
A Survey on Vulnerability of Federated Learning: A Learning Algorithm Perspective Xianghua Xie Chen Hu Hanchi Ren Jingjing Deng FedML AAML 50 19 0 27 Nov 2023
FedBEVT: Federated Learning Bird's Eye View Perception Transformer in Road Traffic Systems Rui Song Runsheng Xu Andreas Festag Jiaqi Ma Alois Knoll FedML 31 25 0 04 Apr 2023
Emerging Threats in Deep Learning-Based Autonomous Driving: A Comprehensive Survey Huiyun Cao Wenlong Zou Yinkun Wang Ting Song Mengjun Liu AAML 54 4 0 19 Oct 2022
Heterogeneous Federated Learning on a Graph Huiyuan Wang Xuyang Zhao Weijie Lin FedML 57 4 0 19 Sep 2022
Federated Transfer Learning with Multimodal Data Yulian Sun FedML 21 4 0 05 Sep 2022
Deep Federated Learning for Autonomous Driving A. Nguyen Tuong Khanh Long Do Minh-Ngoc Tran Binh X. Nguyen C. Duong T. Phan Erman Tjiputra Quang-Dieu Tran FedML 36 109 0 12 Oct 2021
Asynchronous Federated Learning on Heterogeneous Devices: A Survey Chenhao Xu Youyang Qu Yong Xiang Longxiang Gao FedML 104 242 0 09 Sep 2021